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Air temperature is an important meteorological variable in many fields of our life. However, the availability of air temperature measurements over large geographic areas is often limited by the weather stations spatial distribution inadequacy, their low density and difficulties of data quality and collection. In this context, this study consists to develop four simple models to estimate the three components of air temperature (Tmin, Tmax and Tmean) from remotely sensed land surface temperature (Ts) derived from NOAA-AVHRR images, and based on the international Koppen-Geiger climate classification of Morocco. The results confirmed the existence of good relationships between the three components of measured air temperatures and land surface temperature derived from NOAA-AVHRR images for the main four climate classes of Morocco. The coefficient of determination, R2, varied between 0.69 and 0.80 for Tmin versus Ts, between 0.62 and 0.74 for Tmax versus Ts, and between 0.69 and 0.79 for Tmean versus Ts. The root mean square error varied between 3.1 °C and 3.3 °C for Tmin versus Ts, between 3.2 and 4.1 °C for Tmax versus Ts and between 2.7 and 3.4 °C for Tmean versus Ts. K-fold cross validation method was performed to assess the accuracy and the stability of proposed models. The limited number of proposed models is a great advantage to carry further studies requiring air temperature’s components at larger scale.